Final Project: Young Living Pine Project
Ryanne Welch
Project Overview
Young Living, Dr. Rotter and UVU students are working together to study how the phytochemistry of pinyon pine pine cones change as the insect communities of those pine cones change. Unfortunately we are still waiting for the phytochemistry information to come back, but in the mean time we can make some observations of the insect communities in these cones.
Brief Background
Cones were collected from 20 different pinyon pine trees through out a year. Each cone was ranked on a scale of one to three based on stage. A rating of one means to cone is young and closed, two means middle and open, three means old, dry and open. The scales were measured in mm. Then the cones were inspected for insects. The insects were broken down into 6 different groups, one being a “catch-all” other and the rest being different insect types: conophthorus beetle, megastigmus wasp, midge, pinyon bore moth, and spider.
Scale Thickness and Insect Communities
In the end we didn’t have enough information to draw a conclusion for the entire community, so here we look at each insect type individually.
## # A tibble: 2,736 × 3
## ID insect_type n
## <chr> <chr> <int>
## 1 10_April_1 conopthorus_sp_beetle_larva 3
## 2 10_April_1 megastigmus_wasp 3
## 3 10_April_1 midge 3
## 4 10_April_1 pinyon_bore_moth 3
## 5 10_April_1 spider 3
## 6 10_April_1 unknown_seed_insect 3
## 7 10_April_2 conopthorus_sp_beetle_larva 2
## 8 10_April_2 megastigmus_wasp 2
## 9 10_April_2 midge 2
## 10 10_April_2 pinyon_bore_moth 2
## # … with 2,726 more rows## Run 0 stress 0.00134901
## Run 1 stress 0.0002186504
## ... New best solution
## ... Procrustes: rmse 0.04262596 max resid 0.4060861
## Run 2 stress 0.0002020688
## ... New best solution
## ... Procrustes: rmse 0.04709831 max resid 0.4661662
## Run 3 stress 0.0002159847
## ... Procrustes: rmse 0.0552248 max resid 0.6217512
## Run 4 stress 0.0002208511
## ... Procrustes: rmse 0.05465652 max resid 0.5271873
## Run 5 stress 0.0002038439
## ... Procrustes: rmse 0.05342078 max resid 0.6369084
## Run 6 stress 0.0002076246
## ... Procrustes: rmse 0.03275661 max resid 0.3615275
## Run 7 stress 0.0002366391
## ... Procrustes: rmse 0.03177219 max resid 0.3747111
## Run 8 stress 0.000205977
## ... Procrustes: rmse 0.06165003 max resid 0.5200693
## Run 9 stress 0.0002379013
## ... Procrustes: rmse 0.04606095 max resid 0.4300237
## Run 10 stress 0.0002169625
## ... Procrustes: rmse 0.05441093 max resid 0.4737152
## Run 11 stress 0.0002320624
## ... Procrustes: rmse 0.06253164 max resid 0.7201601
## Run 12 stress 0.0002176369
## ... Procrustes: rmse 0.04542522 max resid 0.3972916
## Run 13 stress 0.0001966897
## ... New best solution
## ... Procrustes: rmse 0.06648887 max resid 0.6103006
## Run 14 stress 0.0002325584
## ... Procrustes: rmse 0.06220171 max resid 0.6625143
## Run 15 stress 0.0001849045
## ... New best solution
## ... Procrustes: rmse 0.04713136 max resid 0.5952391
## Run 16 stress 0.0002202375
## ... Procrustes: rmse 0.05824491 max resid 0.5098148
## Run 17 stress 0.0002140508
## ... Procrustes: rmse 0.02748102 max resid 0.2783853
## Run 18 stress 0.0002074014
## ... Procrustes: rmse 0.05347891 max resid 0.5921786
## Run 19 stress 0.0002383263
## ... Procrustes: rmse 0.06657368 max resid 0.651727
## Run 20 stress 0.000252319
## ... Procrustes: rmse 0.05507774 max resid 0.7237888
## *** Best solution was not repeated -- monoMDS stopping criteria:
## 1: no. of iterations >= maxit
## 19: scale factor of the gradient < sfgrmin## [1] 7.5 7.5 7.5 7.5 7.5 7.5 8.0 8.0 8.0 8.0 8.0 8.0 4.0 4.0 4.0 4.0 4.0 4.0
## [19] 7.5 7.5 7.5 7.5 7.5 7.5 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0
## [37] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 7.0 7.0 7.0 7.0 7.0 7.0
## [55] 7.0 7.0 7.0 7.0 7.0 7.0 5.5 5.5 5.5 5.5 5.5 5.5 5.0 5.0 5.0 5.0 5.0 5.0
## [73] 5.5 5.5 5.5 5.5 5.5 5.5 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0
## [91] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0
## [109] 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [127] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0
## [145] 7.0 7.0 7.0 7.0 7.0 7.0 5.0 5.0 5.0 5.0 5.0 5.0 2.0 2.0 2.0 2.0 2.0 2.0
## [163] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [181] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [199] 7.0 7.0 7.0 7.0 7.0 7.0 3.0 3.0 3.0 3.0 3.0 3.0 4.0 4.0 4.0 4.0 4.0 4.0
## [217] 7.0 7.0 7.0 7.0 7.0 7.0 3.0 3.0 3.0 3.0 3.0 3.0 5.0 5.0 5.0 5.0 5.0 5.0
## [235] 7.0 7.0 7.0 7.0 7.0 7.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [253] 5.0 5.0 5.0 5.0 5.0 5.0 3.0 3.0 3.0 3.0 3.0 3.0 6.0 6.0 6.0 6.0 6.0 6.0
## [271] 4.0 4.0 4.0 4.0 4.0 4.0 5.5 5.5 5.5 5.5 5.5 5.5 6.5 6.5 6.5 6.5 6.5 6.5
## [289] 4.5 4.5 4.5 4.5 4.5 4.5 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [307] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [325] 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0
## [343] 3.0 3.0 3.0 3.0 3.0 3.0 4.5 4.5 4.5 4.5 4.5 4.5 4.0 4.0 4.0 4.0 4.0 4.0
## [361] 3.0 3.0 3.0 3.0 3.0 3.0 3.5 3.5 3.5 3.5 3.5 3.5 4.0 4.0 4.0 4.0 4.0 4.0
## [379] 3.5 3.5 3.5 3.5 3.5 3.5 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [397] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [415] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [433] 3.0 3.0 3.0 3.0 3.0 3.0 2.0 2.0 2.0 2.0 2.0 2.0 4.0 4.0 4.0 4.0 4.0 4.0
## [451] 4.5 4.5 4.5 4.5 4.5 4.5 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0
## [469] 3.0 3.0 3.0 3.0 3.0 3.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [487] 6.5 6.5 6.5 6.5 6.5 6.5 4.0 4.0 4.0 4.0 4.0 4.0 5.5 5.5 5.5 5.5 5.5 5.5
## [505] 5.0 5.0 5.0 5.0 5.0 5.0 3.5 3.5 3.5 3.5 3.5 3.5 6.0 6.0 6.0 6.0 6.0 6.0
## [523] 4.0 4.0 4.0 4.0 4.0 4.0 5.5 5.5 5.5 5.5 5.5 5.5 5.0 5.0 5.0 5.0 5.0 5.0
## [541] 4.5 4.5 4.5 4.5 4.5 4.5 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [559] 3.0 3.0 3.0 3.0 3.0 3.0 4.0 4.0 4.0 4.0 4.0 4.0 3.0 3.0 3.0 3.0 3.0 3.0
## [577] 3.0 3.0 3.0 3.0 3.0 3.0 3.5 3.5 3.5 3.5 3.5 3.5 4.0 4.0 4.0 4.0 4.0 4.0
## [595] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [613] 2.5 2.5 2.5 2.5 2.5 2.5 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [631] 6.0 6.0 6.0 6.0 6.0 6.0 4.5 4.5 4.5 4.5 4.5 4.5 5.0 5.0 5.0 5.0 5.0 5.0
## [649] 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0 3.0 3.0 3.0 3.0 3.0 3.0
## [667] 5.0 5.0 5.0 5.0 5.0 5.0 4.5 4.5 4.5 4.5 4.5 4.5 4.0 4.0 4.0 4.0 4.0 4.0
## [685] 6.0 6.0 6.0 6.0 6.0 6.0 4.5 4.5 4.5 4.5 4.5 4.5 6.5 6.5 6.5 6.5 6.5 6.5
## [703] 5.5 5.5 5.5 5.5 5.5 5.5 6.0 6.0 6.0 6.0 6.0 6.0 4.5 4.5 4.5 4.5 4.5 4.5
## [721] 3.0 3.0 3.0 3.0 3.0 3.0 3.5 3.5 3.5 3.5 3.5 3.5 5.0 5.0 5.0 5.0 5.0 5.0
## [739] 7.0 7.0 7.0 7.0 7.0 7.0 4.0 4.0 4.0 4.0 4.0 4.0 3.5 3.5 3.5 3.5 3.5 3.5
## [757] 4.0 4.0 4.0 4.0 4.0 4.0 6.5 6.5 6.5 6.5 6.5 6.5 6.0 6.0 6.0 6.0 6.0 6.0
## [775] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [793] 2.5 2.5 2.5 2.5 2.5 2.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5
## [811] 4.0 4.0 4.0 4.0 4.0 4.0 3.5 3.5 3.5 3.5 3.5 3.5 4.0 4.0 4.0 4.0 4.0 4.0
## [829] 3.0 3.0 3.0 3.0 3.0 3.0 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0
## [847] 7.5 7.5 7.5 7.5 7.5 7.5 4.5 4.5 4.5 4.5 4.5 4.5 5.5 5.5 5.5 5.5 5.5 5.5
## [865] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [883] 5.5 5.5 5.5 5.5 5.5 5.5 4.5 4.5 4.5 4.5 4.5 4.5 4.0 4.0 4.0 4.0 4.0 4.0
## [901] 3.0 3.0 3.0 3.0 3.0 3.0 5.0 5.0 5.0 5.0 5.0 5.0 4.5 4.5 4.5 4.5 4.5 4.5
## [919] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [937] 2.5 2.5 2.5 2.5 2.5 2.5 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0
## [955] 3.0 3.0 3.0 3.0 3.0 3.0 5.0 5.0 5.0 5.0 5.0 5.0 5.5 5.5 5.5 5.5 5.5 5.5
## [973] 3.0 3.0 3.0 3.0 3.0 3.0 5.5 5.5 5.5 5.5 5.5 5.5 3.0 3.0 3.0 3.0 3.0 3.0
## [991] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.5 4.5 4.5 4.5 4.5 4.5
## [1009] 5.0 5.0 5.0 5.0 5.0 5.0 3.0 3.0 3.0 3.0 3.0 3.0 7.0 7.0 7.0 7.0 7.0 7.0
## [1027] 6.0 6.0 6.0 6.0 6.0 6.0 5.5 5.5 5.5 5.5 5.5 5.5 6.0 6.0 6.0 6.0 6.0 6.0
## [1045] 4.5 4.5 4.5 4.5 4.5 4.5 5.5 5.5 5.5 5.5 5.5 5.5 5.0 5.0 5.0 5.0 5.0 5.0
## [1063] 4.5 4.5 4.5 4.5 4.5 4.5 7.0 7.0 7.0 7.0 7.0 7.0 5.5 5.5 5.5 5.5 5.5 5.5
## [1081] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 4.5 4.5 4.5 4.5 4.5 4.5
## [1099] 5.0 5.0 5.0 5.0 5.0 5.0 5.5 5.5 5.5 5.5 5.5 5.5 6.5 6.5 6.5 6.5 6.5 6.5
## [1117] 5.5 5.5 5.5 5.5 5.5 5.5 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [1135] 4.5 4.5 4.5 4.5 4.5 4.5 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [1153] 5.0 5.0 5.0 5.0 5.0 5.0 3.5 3.5 3.5 3.5 3.5 3.5 4.0 4.0 4.0 4.0 4.0 4.0
## [1171] 4.0 4.0 4.0 4.0 4.0 4.0 3.5 3.5 3.5 3.5 3.5 3.5 4.5 4.5 4.5 4.5 4.5 4.5
## [1189] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 3.0 3.0 3.0 3.0 3.0 3.0
## [1207] 4.0 4.0 4.0 4.0 4.0 4.0 7.0 7.0 7.0 7.0 7.0 7.0 4.0 4.0 4.0 4.0 4.0 4.0
## [1225] 5.0 5.0 5.0 5.0 5.0 5.0 3.0 3.0 3.0 3.0 3.0 3.0 4.0 4.0 4.0 4.0 4.0 4.0
## [1243] 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 6.0 6.0 6.0 6.0 6.0 6.0
## [1261] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 3.0 3.0 3.0 3.0 3.0 3.0
## [1279] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [1297] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [1315] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 4.5 4.5 4.5 4.5 4.5 4.5
## [1333] 4.0 4.0 4.0 4.0 4.0 4.0 3.5 3.5 3.5 3.5 3.5 3.5 2.5 2.5 2.5 2.5 2.5 2.5
## [1351] 5.0 5.0 5.0 5.0 5.0 5.0 4.5 4.5 4.5 4.5 4.5 4.5 5.5 5.5 5.5 5.5 5.5 5.5
## [1369] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 4.5 4.5 4.5 4.5 4.5 4.5
## [1387] 5.0 5.0 5.0 5.0 5.0 5.0 5.5 5.5 5.5 5.5 5.5 5.5 4.0 4.0 4.0 4.0 4.0 4.0
## [1405] 4.5 4.5 4.5 4.5 4.5 4.5 3.0 3.0 3.0 3.0 3.0 3.0 5.5 5.5 5.5 5.5 5.5 5.5
## [1423] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [1441] 5.5 5.5 5.5 5.5 5.5 5.5 3.5 3.5 3.5 3.5 3.5 3.5 4.0 4.0 4.0 4.0 4.0 4.0
## [1459] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [1477] 4.5 4.5 4.5 4.5 4.5 4.5 3.5 3.5 3.5 3.5 3.5 3.5 6.5 6.5 6.5 6.5 6.5 6.5
## [1495] 3.0 3.0 3.0 3.0 3.0 3.0 5.5 5.5 5.5 5.5 5.5 5.5 6.0 6.0 6.0 6.0 6.0 6.0
## [1513] 5.5 5.5 5.5 5.5 5.5 5.5 3.5 3.5 3.5 3.5 3.5 3.5 5.0 5.0 5.0 5.0 5.0 5.0
## [1531] 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5
## [1549] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [1567] 3.0 3.0 3.0 3.0 3.0 3.0 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5
## [1585] 5.0 5.0 5.0 5.0 5.0 5.0 4.5 4.5 4.5 4.5 4.5 4.5 6.0 6.0 6.0 6.0 6.0 6.0
## [1603] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [1621] 7.0 7.0 7.0 7.0 7.0 7.0 5.5 5.5 5.5 5.5 5.5 5.5 6.5 6.5 6.5 6.5 6.5 6.5
## [1639] 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [1657] 6.5 6.5 6.5 6.5 6.5 6.5 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0
## [1675] 9.0 9.0 9.0 9.0 9.0 9.0 9.5 9.5 9.5 9.5 9.5 9.5 7.0 7.0 7.0 7.0 7.0 7.0
## [1693] 8.0 8.0 8.0 8.0 8.0 8.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0
## [1711] 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0 5.5 5.5 5.5 5.5 5.5 5.5
## [1729] 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [1747] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0
## [1765] 7.0 7.0 7.0 7.0 7.0 7.0 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0
## [1783] 4.5 4.5 4.5 4.5 4.5 4.5 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [1801] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [1819] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0
## [1837] 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0 6.5 6.5 6.5 6.5 6.5 6.5
## [1855] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [1873] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [1891] 5.5 5.5 5.5 5.5 5.5 5.5 3.5 3.5 3.5 3.5 3.5 3.5 4.5 4.5 4.5 4.5 4.5 4.5
## [1909] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 7.0 7.0 7.0 7.0 7.0 7.0
## [1927] 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0
## [1945] 3.0 3.0 3.0 3.0 3.0 3.0 4.5 4.5 4.5 4.5 4.5 4.5 3.0 3.0 3.0 3.0 3.0 3.0
## [1963] 5.5 5.5 5.5 5.5 5.5 5.5 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0
## [1981] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [1999] 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0 7.5 7.5 7.5 7.5 7.5 7.5
## [2017] 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0 9.0 9.0 9.0 9.0 9.0 9.0
## [2035] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [2053] 3.0 3.0 3.0 3.0 3.0 3.0 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0
## [2071] 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0
## [2089] 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [2107] 5.5 5.5 5.5 5.5 5.5 5.5 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [2125] 3.5 3.5 3.5 3.5 3.5 3.5 5.0 5.0 5.0 5.0 5.0 5.0 5.5 5.5 5.5 5.5 5.5 5.5
## [2143] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [2161] 8.0 8.0 8.0 8.0 8.0 8.0 6.0 6.0 6.0 6.0 6.0 6.0 8.0 8.0 8.0 8.0 8.0 8.0
## [2179] 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0
## [2197] 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0
## [2215] 7.0 7.0 7.0 7.0 7.0 7.0 6.5 6.5 6.5 6.5 6.5 6.5 7.0 7.0 7.0 7.0 7.0 7.0
## [2233] 7.0 7.0 7.0 7.0 7.0 7.0 8.0 8.0 8.0 8.0 8.0 8.0 7.0 7.0 7.0 7.0 7.0 7.0
## [2251] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [2269] 7.0 7.0 7.0 7.0 7.0 7.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [2287] 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0
## [2305] 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0
## [2323] 9.0 9.0 9.0 9.0 9.0 9.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0
## [2341] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [2359] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [2377] 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0
## [2395] 8.0 8.0 8.0 8.0 8.0 8.0 5.0 5.0 5.0 5.0 5.0 5.0 7.0 7.0 7.0 7.0 7.0 7.0
## [2413] 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0
## [2431] 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 5.0 5.0 5.0 5.0 5.0 5.0
## [2449] 7.0 7.0 7.0 7.0 7.0 7.0 6.5 6.5 6.5 6.5 6.5 6.5 6.0 6.0 6.0 6.0 6.0 6.0
## [2467] 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0
## [2485] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [2503] 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [2521] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [2539] 2.0 2.0 2.0 2.0 2.0 2.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [2557] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0
## [2575] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [2593] 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0 4.0 4.0 4.0 4.0 4.0 4.0
## [2611] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [2629] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [2647] 5.0 5.0 5.0 5.0 5.0 5.0 9.0 9.0 9.0 9.0 9.0 9.0 5.0 5.0 5.0 5.0 5.0 5.0
## [2665] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 3.0 3.0 3.0 3.0 3.0 3.0
## [2683] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [2701] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [2719] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.5 6.5 6.5 6.5 6.5 6.5
## [2737] 4.0 4.0 4.0 4.0 4.0 4.0 7.0 7.0 7.0 7.0 7.0 7.0 5.0 5.0 5.0 5.0 5.0 5.0
## [2755] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0
## [2773] 5.0 5.0 5.0 5.0 5.0 5.0 5.5 5.5 5.5 5.5 5.5 5.5 6.0 6.0 6.0 6.0 6.0 6.0
## [2791] 7.0 7.0 7.0 7.0 7.0 7.0 8.0 8.0 8.0 8.0 8.0 8.0 6.0 6.0 6.0 6.0 6.0 6.0
## [2809] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [2827] 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [2845] 5.5 5.5 5.5 5.5 5.5 5.5 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [2863] 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [2881] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [2899] 5.0 5.0 5.0 5.0 5.0 5.0 8.0 8.0 8.0 8.0 8.0 8.0 6.0 6.0 6.0 6.0 6.0 6.0
## [2917] 3.0 3.0 3.0 3.0 3.0 3.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [2935] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0
## [2953] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [2971] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [2989] 7.0 7.0 7.0 7.0 7.0 7.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [3007] 7.0 7.0 7.0 7.0 7.0 7.0 9.0 9.0 9.0 9.0 9.0 9.0 6.0 6.0 6.0 6.0 6.0 6.0
## [3025] 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [3043] 6.0 6.0 6.0 6.0 6.0 6.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0
## [3061] 8.0 8.0 8.0 8.0 8.0 8.0 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0
## [3079] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 7.0 7.0 7.0 7.0 7.0 7.0
## [3097] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [3115] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0
## [3133] 7.0 7.0 7.0 7.0 7.0 7.0 5.5 5.5 5.5 5.5 5.5 5.5 6.0 6.0 6.0 6.0 6.0 6.0
## [3151] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 8.0 8.0 8.0 8.0 8.0 8.0
## [3169] 7.0 7.0 7.0 7.0 7.0 7.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [3187] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [3205] 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [3223] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0
## [3241] 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0 2.3 2.3 2.3 2.3 2.3 2.3
## [3259] 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0
## [3277] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0
## [3295] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [3313] 3.0 3.0 3.0 3.0 3.0 3.0 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0
## [3331] 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0
## [3349] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [3367] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [3385] 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0
## [3403] 3.0 3.0 3.0 3.0 3.0 3.0 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0
## [3421] 7.0 7.0 7.0 7.0 7.0 7.0 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0
## [3439] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 3.0 3.0 3.0 3.0 3.0 3.0
## [3457] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [3475] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [3493] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [3511] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [3529] 5.0 5.0 5.0 5.0 5.0 5.0 3.0 3.0 3.0 3.0 3.0 3.0 6.0 6.0 6.0 6.0 6.0 6.0
## [3547] 6.0 6.0 6.0 6.0 6.0 6.0 3.0 3.0 3.0 3.0 3.0 3.0 2.0 2.0 2.0 2.0 2.0 2.0
## [3565] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 3.0 3.0 3.0 3.0 3.0 3.0
## [3583] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 3.0 3.0 3.0 3.0 3.0 3.0
## [3601] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [3619] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [3637] 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0 5.0 5.0 5.0 5.0 5.0 5.0
## [3655] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 3.0 3.0 3.0 3.0 3.0 3.0
## [3673] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0
## [3691] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [3709] 4.0 4.0 4.0 4.0 4.0 4.0 3.0 3.0 3.0 3.0 3.0 3.0 4.0 4.0 4.0 4.0 4.0 4.0
## [3727] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 2.0 2.0 2.0 2.0 2.0 2.0
## [3745] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [3763] 4.0 4.0 4.0 4.0 4.0 4.0 3.0 3.0 3.0 3.0 3.0 3.0 4.0 4.0 4.0 4.0 4.0 4.0
## [3781] 7.0 7.0 7.0 7.0 7.0 7.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [3799] 5.0 5.0 5.0 5.0 5.0 5.0 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0
## [3817] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [3835] 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [3853] 4.0 4.0 4.0 4.0 4.0 4.0 3.0 3.0 3.0 3.0 3.0 3.0 5.0 5.0 5.0 5.0 5.0 5.0
## [3871] 8.0 8.0 8.0 8.0 8.0 8.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [3889] 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [3907] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [3925] 4.0 4.0 4.0 4.0 4.0 4.0 3.0 3.0 3.0 3.0 3.0 3.0 5.0 5.0 5.0 5.0 5.0 5.0
## [3943] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [3961] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 3.0 3.0 3.0 3.0 3.0 3.0
## [3979] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 0.0 0.0 0.0 0.0 0.0 0.0
## [3997] 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0
## [4015] 7.0 7.0 7.0 7.0 7.0 7.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [4033] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [4051] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [4069] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [4087] 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0
## [4105] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [4123] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [4141] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [4159] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [4177] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [4195] 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0
## [4213] 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0
## [4231] 7.0 7.0 7.0 7.0 7.0 7.0 8.0 8.0 8.0 8.0 8.0 8.0 7.0 7.0 7.0 7.0 7.0 7.0
## [4249] 5.0 5.0 5.0 5.0 5.0 5.0 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0
## [4267] 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [4285] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 3.0 3.0 3.0 3.0 3.0 3.0
## [4303] 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [4321] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [4339] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [4357] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0
## [4375] 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 5.0 5.0 5.0 5.0 5.0 5.0
## [4393] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [4411] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [4429] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [4447] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [4465] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [4483] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [4501] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [4519] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0
## [4537] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [4555] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [4573] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [4591] 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0
## [4609] 5.0 5.0 5.0 5.0 5.0 5.0 3.0 3.0 3.0 3.0 3.0 3.0 4.0 4.0 4.0 4.0 4.0 4.0
## [4627] 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0
## [4645] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 3.0 3.0 3.0 3.0 3.0 3.0
## [4663] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [4681] 9.0 9.0 9.0 9.0 9.0 9.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [4699] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [4717] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0
## [4735] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [4753] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [4771] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [4789] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0
## [4807] 8.0 8.0 8.0 8.0 8.0 8.0 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0
## [4825] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [4843] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0
## [4861] 7.0 7.0 7.0 7.0 7.0 7.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [4879] 8.0 8.0 8.0 8.0 8.0 8.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [4897] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [4915] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [4933] 0.0 0.0 0.0 0.0 0.0 0.0 8.0 8.0 8.0 8.0 8.0 8.0 6.0 6.0 6.0 6.0 6.0 6.0
## [4951] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [4969] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 3.0 3.0 3.0 3.0 3.0 3.0
## [4987] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [5005] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [5023] 4.0 4.0 4.0 4.0 4.0 4.0 0.0 0.0 0.0 0.0 0.0 0.0 5.0 5.0 5.0 5.0 5.0 5.0
## [5041] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [5059] 5.0 5.0 5.0 5.0 5.0 5.0 7.0 7.0 7.0 7.0 7.0 7.0 5.0 5.0 5.0 5.0 5.0 5.0
## [5077] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [5095] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [5113] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [5131] 6.0 6.0 6.0 6.0 6.0 6.0 8.0 8.0 8.0 8.0 8.0 8.0 5.0 5.0 5.0 5.0 5.0 5.0
## [5149] 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [5167] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [5185] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [5203] 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [5221] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [5239] 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0
## [5257] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [5275] 3.0 3.0 3.0 3.0 3.0 3.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [5293] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [5311] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [5329] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [5347] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0
## [5365] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0
## [5383] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [5401] 3.0 3.0 3.0 3.0 3.0 3.0 2.0 2.0 2.0 2.0 2.0 2.0 6.0 6.0 6.0 6.0 6.0 6.0
## [5419] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [5437] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [5455] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [5473] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0
## [5491] 7.0 7.0 7.0 7.0 7.0 7.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0
## [5509] 5.0 5.0 5.0 5.0 5.0 5.0 7.0 7.0 7.0 7.0 7.0 7.0 5.0 5.0 5.0 5.0 5.0 5.0
## [5527] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0
## [5545] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0
## [5563] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [5581] 3.0 3.0 3.0 3.0 3.0 3.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [5599] 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0
## [5617] 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 5.0 5.0 5.0 5.0 5.0 5.0
## [5635] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 8.0 8.0 8.0 8.0 8.0 8.0
## [5653] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [5671] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [5689] 5.0 5.0 5.0 5.0 5.0 5.0 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0
## [5707] 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0
## [5725] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [5743] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [5761] 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 8.0 8.0 8.0 8.0 8.0 8.0
## [5779] 5.0 5.0 5.0 5.0 5.0 5.0 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0
## [5797] 7.0 7.0 7.0 7.0 7.0 7.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [5815] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [5833] 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0
## [5851] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [5869] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 3.0 3.0 3.0 3.0 3.0 3.0
## [5887] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [5905] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [5923] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0
## [5941] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [5959] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0
## [5977] 2.0 2.0 2.0 2.0 2.0 2.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [5995] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [6013] 8.0 8.0 8.0 8.0 8.0 8.0 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0
## [6031] 3.0 3.0 3.0 3.0 3.0 3.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [6049] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [6067] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [6085] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [6103] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [6121] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 2.0 2.0 2.0 2.0 2.0 2.0
## [6139] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [6157] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [6175] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [6193] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [6211] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [6229] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [6247] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [6265] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [6283] 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0 3.0 3.0 3.0 3.0 3.0 3.0
## [6301] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [6319] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [6337] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [6355] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [6373] 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0
## [6391] 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0
## [6409] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0
## [6427] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [6445] 4.0 4.0 4.0 4.0 4.0 4.0 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0
## [6463] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [6481] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [6499] 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [6517] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0
## [6535] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [6553] 5.0 5.0 5.0 5.0 5.0 5.0 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5
## [6571] 5.5 5.5 5.5 5.5 5.5 5.5 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [6589] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [6607] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [6625] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0
## [6643] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [6661] 3.0 3.0 3.0 3.0 3.0 3.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [6679] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [6697] 4.0 4.0 4.0 4.0 4.0 4.0 3.0 3.0 3.0 3.0 3.0 3.0 6.0 6.0 6.0 6.0 6.0 6.0
## [6715] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [6733] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [6751] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [6769] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [6787] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [6805] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [6823] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [6841] 1.0 1.0 1.0 1.0 1.0 1.0 2.0 2.0 2.0 2.0 2.0 2.0 4.0 4.0 4.0 4.0 4.0 4.0
## [6859] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [6877] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [6895] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [6913] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [6931] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [6949] 4.0 4.0 4.0 4.0 4.0 4.0 4.5 4.5 4.5 4.5 4.5 4.5 6.0 6.0 6.0 6.0 6.0 6.0
## [6967] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 6.5 6.5 6.5 6.5 6.5 6.5
## [6985] 6.0 6.0 6.0 6.0 6.0 6.0 5.5 5.5 5.5 5.5 5.5 5.5 5.0 5.0 5.0 5.0 5.0 5.0
## [7003] 6.0 6.0 6.0 6.0 6.0 6.0 5.5 5.5 5.5 5.5 5.5 5.5 7.0 7.0 7.0 7.0 7.0 7.0
## [7021] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [7039] 5.0 5.0 5.0 5.0 5.0 5.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0
## [7057] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [7075] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [7093] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 7.0 7.0 7.0 7.0 7.0 7.0
## [7111] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [7129] 5.0 5.0 5.0 5.0 5.0 5.0 4.5 4.5 4.5 4.5 4.5 4.5 5.0 5.0 5.0 5.0 5.0 5.0
## [7147] 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 5.0 5.0 5.0 5.0 5.0 5.0
## [7165] 5.5 5.5 5.5 5.5 5.5 5.5 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [7183] 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [7201] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [7219] 5.5 5.5 5.5 5.5 5.5 5.5 4.5 4.5 4.5 4.5 4.5 4.5 5.0 5.0 5.0 5.0 5.0 5.0
## [7237] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [7255] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [7273] 5.0 5.0 5.0 5.0 5.0 5.0 5.5 5.5 5.5 5.5 5.5 5.5 6.0 6.0 6.0 6.0 6.0 6.0
## [7291] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [7309] 3.0 3.0 3.0 3.0 3.0 3.0 5.5 5.5 5.5 5.5 5.5 5.5 5.0 5.0 5.0 5.0 5.0 5.0
## [7327] 5.5 5.5 5.5 5.5 5.5 5.5 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [7345] 5.0 5.0 5.0 5.0 5.0 5.0 4.5 4.5 4.5 4.5 4.5 4.5 5.0 5.0 5.0 5.0 5.0 5.0
## [7363] 5.5 5.5 5.5 5.5 5.5 5.5 4.5 4.5 4.5 4.5 4.5 4.5 5.0 5.0 5.0 5.0 5.0 5.0
## [7381] 5.0 5.0 5.0 5.0 5.0 5.0 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5
## [7399] 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 3.0 3.0 3.0 3.0 3.0 3.0
## [7417] 4.0 4.0 4.0 4.0 4.0 4.0 3.0 3.0 3.0 3.0 3.0 3.0 4.0 4.0 4.0 4.0 4.0 4.0
## [7435] 3.5 3.5 3.5 3.5 3.5 3.5 3.0 3.0 3.0 3.0 3.0 3.0 3.5 3.5 3.5 3.5 3.5 3.5
## [7453] 5.5 5.5 5.5 5.5 5.5 5.5 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [7471] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 3.0 3.0 3.0 3.0 3.0 3.0
## [7489] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0
## [7507] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 4.5 4.5 4.5 4.5 4.5 4.5
## [7525] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 2.0 2.0 2.0 2.0 2.0 2.0
## [7543] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [7561] 2.0 2.0 2.0 2.0 2.0 2.0 4.5 4.5 4.5 4.5 4.5 4.5 5.0 5.0 5.0 5.0 5.0 5.0
## [7579] 5.5 5.5 5.5 5.5 5.5 5.5 4.5 4.5 4.5 4.5 4.5 4.5 5.0 5.0 5.0 5.0 5.0 5.0
## [7597] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 4.5 4.5 4.5 4.5 4.5 4.5
## [7615] 5.5 5.5 5.5 5.5 5.5 5.5 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0
## [7633] 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.5 5.0 5.0 5.0 5.0 5.0 5.0
## [7651] 5.0 5.0 5.0 5.0 5.0 5.0 5.5 5.5 5.5 5.5 5.5 5.5 5.0 5.0 5.0 5.0 5.0 5.0
## [7669] 3.0 3.0 3.0 3.0 3.0 3.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [7687] 5.5 5.5 5.5 5.5 5.5 5.5 4.0 4.0 4.0 4.0 4.0 4.0 5.5 5.5 5.5 5.5 5.5 5.5
## [7705] 4.5 4.5 4.5 4.5 4.5 4.5 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [7723] 5.0 5.0 5.0 5.0 5.0 5.0 5.5 5.5 5.5 5.5 5.5 5.5 5.0 5.0 5.0 5.0 5.0 5.0
## [7741] 6.0 6.0 6.0 6.0 6.0 6.0 5.5 5.5 5.5 5.5 5.5 5.5 5.0 5.0 5.0 5.0 5.0 5.0
## [7759] 4.5 4.5 4.5 4.5 4.5 4.5 5.0 5.0 5.0 5.0 5.0 5.0 4.5 4.5 4.5 4.5 4.5 4.5
## [7777] 4.5 4.5 4.5 4.5 4.5 4.5 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [7795] 4.5 4.5 4.5 4.5 4.5 4.5 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [7813] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [7831] 7.0 7.0 7.0 7.0 7.0 7.0 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5
## [7849] 6.0 6.0 6.0 6.0 6.0 6.0 7.0 7.0 7.0 7.0 7.0 7.0 3.0 3.0 3.0 3.0 3.0 3.0
## [7867] 7.0 7.0 7.0 7.0 7.0 7.0 8.0 8.0 8.0 8.0 8.0 8.0 6.0 6.0 6.0 6.0 6.0 6.0
## [7885] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [7903] 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 5.0 5.0 5.0 5.0 5.0 5.0
## [7921] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 3.0 3.0 3.0 3.0 3.0 3.0
## [7939] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [7957] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 3.0 3.0 3.0 3.0 3.0 3.0
## [7975] 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## [7993] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [8011] 5.0 5.0 5.0 5.0 5.0 5.0 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0
## [8029] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [8047] 7.0 7.0 7.0 7.0 7.0 7.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [8065] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [8083] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 4.0 4.0 4.0 4.0 4.0 4.0
## [8101] 5.0 5.0 5.0 5.0 5.0 5.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [8119] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [8137] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 4.5 4.5 4.5 4.5 4.5 4.5
## [8155] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [8173] 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [8191] 6.0 6.0 6.0 6.0 6.0 6.0 4.5 4.5 4.5 4.5 4.5 4.5 5.0 5.0 5.0 5.0 5.0 5.0
## [8209] 7.0 7.0 7.0 7.0 7.0 7.0 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0
## [8227] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 5.0 5.0 5.0 5.0 5.0 5.0
## [8245] 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0
## [8263] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [8281] 4.0 4.0 4.0 4.0 4.0 4.0 3.0 3.0 3.0 3.0 3.0 3.0 4.5 4.5 4.5 4.5 4.5 4.5
## [8299] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0
## [8317] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [8335] 4.0 4.0 4.0 4.0 4.0 4.0 4.5 4.5 4.5 4.5 4.5 4.5 3.5 3.5 3.5 3.5 3.5 3.5
## [8353] 5.0 5.0 5.0 5.0 5.0 5.0 4.0 4.0 4.0 4.0 4.0 4.0 4.5 4.5 4.5 4.5 4.5 4.5
## [8371] 5.0 5.0 5.0 5.0 5.0 5.0 4.5 4.5 4.5 4.5 4.5 4.5 5.0 5.0 5.0 5.0 5.0 5.0
## [8389] 4.0 4.0 4.0 4.0 4.0 4.0 3.0 3.0 3.0 3.0 3.0 3.0 4.0 4.0 4.0 4.0 4.0 4.0
## [8407] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [8425] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [8443] 4.5 4.5 4.5 4.5 4.5 4.5 5.0 5.0 5.0 5.0 5.0 5.0 4.5 4.5 4.5 4.5 4.5 4.5
## [8461] 2.5 2.5 2.5 2.5 2.5 2.5 5.0 5.0 5.0 5.0 5.0 5.0 3.5 3.5 3.5 3.5 3.5 3.5
## [8479] 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 5.0 5.0 5.0 5.0 5.0 5.0
## [8497] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [8515] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [8533] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 7.0 7.0 7.0 7.0 7.0 7.0
## [8551] 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [8569] 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 5.0 5.0 5.0 5.0 5.0 5.0
## [8587] 4.5 4.5 4.5 4.5 4.5 4.5 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0
## [8605] 4.0 4.0 4.0 4.0 4.0 4.0 5.0 5.0 5.0 5.0 5.0 5.0 4.5 4.5 4.5 4.5 4.5 4.5
## [8623] 5.5 5.5 5.5 5.5 5.5 5.5 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 999
##
## adonis2(formula = wide[newkeepers, -1] ~ thickness[newkeepers])
## Df SumOfSqs R2 F Pr(>F)
## thickness[newkeepers] 1 0.198 0.0034 0.7059 0.547
## Residual 207 57.975 0.9966
## Total 208 58.173 1.0000Cone Stage and Insect Communities
Insect Communities Over Time
